Data-independent acquisition method for ubiquitinome analysis reveals regulation of circadian biology

Data-independent acquisition: A milestone and prospect in clinical mass spectrometry-based proteomics

Data-independent acquisition (DIA) has revolutionized the field of mass spectrometry (MS)-based proteomics over the past few years. DIA stands out for its ability to systematically sample all peptides in a given mass-to-charge range, allowing an unbiased acquisition of proteomics data. This greatly mitigates the issue of missing values and significantly enhances quantitative accuracy, precision, and reproducibility compared to many traditional methods. This review focuses on the critical role of DIA analysis software tools, primarily focusing on their capabilities and the challenges they address in proteomic research. Advances in MS technology, such as trapped ion mobility spectrometry, or high field asymmetric waveform ion mobility spectrometry require sophisticated analysis software capable of handling the increased data complexity and exploiting the full potential of DIA. We identify and critically evaluate leading software tools in the DIA landscape, discussing their unique features, and the reliability of their quantitative and qualitative outputs. We present the biological and clinical relevance of DIA-MS and discuss crucial publications that paved the way for in-depth proteomic characterization in patient-derived specimens. Furthermore, we provide a perspective on emerging trends in clinical applications and present upcoming challenges including standardization and certification of MS-based acquisition strategies in molecular diagnostics. While we emphasize the need for continuous development of software tools to keep pace with evolving technologies, we advise researchers against uncritically accepting the results from DIA software tools. Each tool may have its own biases, and some may not be as sensitive or reliable as others. Our overarching recommendation for both researchers and clinicians is to employ multiple DIA analysis tools, utilizing orthogonal analysis approaches to enhance the robustness and reliability of their findings.

Exploring affinity chromatography in proteomics: A comprehensive review

Over the past decades, the proteomics field has undergone rapid growth. Progress in mass spectrometry and bioinformatics, together with separation methods, has brought many innovative approaches to the study of the molecular biology of the cell. The potential of affinity chromatography was recognized immediately after its first application in proteomics, and since that time, it has become one of the cornerstones of many proteomic protocols. Indeed, this chromatographic technique exploiting the specific binding between two molecules has been employed for numerous purposes, from selective removal of interfering (over)abundant proteins or enrichment of scarce biomarkers in complex biological samples to mapping the post-translational modifications and protein interactions with other proteins, nucleic acids or biologically active small molecules. This review presents a comprehensive survey of this versatile analytical tool in current proteomics. To navigate the reader, the haphazard space of affinity separations is classified according to the experiment's aims and the separated molecule's nature. Different types of available ligands and experimental strategies are discussed in further detail for each of the mentioned procedures.

Global, site-resolved analysis of ubiquitylation occupancy and turnover rate reveals systems properties

Ubiquitylation regulates most proteins and biological processes in a eukaryotic cell. However, the site-specific occupancy (stoichiometry) and turnover rate of ubiquitylation have not been quantified. Here we present an integrated picture of the global ubiquitylation site occupancy and half-life. Ubiquitylation site occupancy spans over four orders of magnitude, but the median ubiquitylation site occupancy is three orders of magnitude lower than that of phosphorylation. The occupancy, turnover rate, and regulation of sites by proteasome inhibitors are strongly interrelated, and these attributes distinguish sites involved in proteasomal degradation and cellular signaling. Sites in structured protein regions exhibit longer half-lives and stronger upregulation by proteasome inhibitors than sites in unstructured regions. Importantly, we discovered a surveillance mechanism that rapidly and site-indiscriminately deubiquitylates all ubiquitin-specific E1 and E2 enzymes, protecting them against accumulation of bystander ubiquitylation. The work provides a systems-scale, quantitative view of ubiquitylation properties and reveals general principles of ubiquitylation-dependent governance.

Circadian regulation of macromolecular complex turnover and proteome renewal

Although costly to maintain, protein homeostasis is indispensable for normal cellular function and long-term health. In mammalian cells and tissues, daily variation in global protein synthesis has been observed, but its utility and consequences for proteome integrity are not fully understood. Using several different pulse-labelling strategies, here we gain direct insight into the relationship between protein synthesis and abundance proteome-wide. We show that protein degradation varies in-phase with protein synthesis, facilitating rhythms in turnover rather than abundance. This results in daily consolidation of proteome renewal whilst minimising changes in composition. Coupled rhythms in synthesis and turnover are especially salient to the assembly of macromolecular protein complexes, particularly the ribosome, the most abundant species of complex in the cell. Daily turnover and proteasomal degradation rhythms render cells and mice more sensitive to proteotoxic stress at specific times of day, potentially contributing to daily rhythms in the efficacy of proteasomal inhibitors against cancer. Our findings suggest that circadian rhythms function to minimise the bioenergetic cost of protein homeostasis through temporal consolidation of protein turnover.

Circadian rhythms in solid organ transplantation

Circadian rhythms are daily cycles in physiology that can affect medical interventions. This review considers how these rhythms may relate to solid organ transplantation. It begins by summarizing the mechanism for circadian rhythm generation known as the molecular clock, and basic research connecting the clock to biological activities germane to organ acceptance. Next follows a review of clinical evidence relating time of day to adverse transplantation outcomes. The concluding section discusses knowledge gaps and practical areas where applying circadian biology might improve transplantation success.

Decoding the ubiquitin landscape by cutting-edge ubiquitinomic approaches

Functional consequences of protein ubiquitination have gone far beyond the degradation regulation as was initially imagined during its discovery 40 years back. The state-of-the-art has revealed the plethora of signaling pathways that are largely regulated by ubiquitination process in eukaryotes. To no surprise, ubiquitination is often dysregulated in many human diseases, including cancer, neurodegeneration and infection. Hence it has become a major focus with high-gain research value for many investigators to unravel new proteoforms, that are the targets of this ubiquitination modification. Despite many biochemical or proteomic approaches available for ubiquitination detection, mass-spectrometry stood out to be the most efficient and transformative technology to read this complex modification script. Here in this review, we have discussed how different ubiquitin codes can be decoded qualitatively and quantitatively following various sequential proteomic approaches to date reported and indicated the current limitations with scope for improvements.

Prediction of glycopeptide fragment mass spectra by deep learning

Deep learning has achieved a notable success in mass spectrometry-based proteomics and is now emerging in glycoproteomics. While various deep learning models can predict fragment mass spectra of peptides with good accuracy, they cannot cope with the non-linear glycan structure in an intact glycopeptide. Herein, we present DeepGlyco, a deep learning-based approach for the prediction of fragment spectra of intact glycopeptides. Our model adopts tree-structured long-short term memory networks to process the glycan moiety and a graph neural network architecture to incorporate potential fragmentation pathways of a specific glycan structure. This feature is beneficial to model explainability and differentiation ability of glycan structural isomers. We further demonstrate that predicted spectral libraries can be used for data-independent acquisition glycoproteomics as a supplement for library completeness. We expect that this work will provide a valuable deep learning resource for glycoproteomics.

The logic of protein post-translational modifications (PTMs): Chemistry, mechanisms and evolution of protein regulation through covalent attachments

Protein post-translational modifications (PTMs) play a crucial role in all cellular functions by regulating protein activity, interactions and half-life. Despite the enormous diversity of modifications, various PTM systems show parallels in their chemical and catalytic underpinnings. Here, focussing on modifications that involve the addition of new elements to amino-acid sidechains, I describe historical milestones and fundamental concepts that support the current understanding of PTMs. The historical survey covers selected key research programmes, including the study of protein phosphorylation as a regulatory switch, protein ubiquitylation as a degradation signal and histone modifications as a functional code. The contribution of crucial techniques for studying PTMs is also discussed. The central part of the essay explores shared chemical principles and catalytic strategies observed across diverse PTM systems, together with mechanisms of substrate selection, the reversibility of PTMs by erasers and the recognition of PTMs by reader domains. Similarities in the basic chemical mechanism are highlighted and their implications are discussed. The final part is dedicated to the evolutionary trajectories of PTM systems, beginning with their possible emergence in the context of rivalry in the prokaryotic world. Together, the essay provides a unified perspective on the diverse world of major protein modifications.

Deciphering non-canonical ubiquitin signaling: biology and methodology

Ubiquitination is a dynamic post-translational modification that regulates virtually all cellular processes by modulating function, localization, interactions and turnover of thousands of substrates. Canonical ubiquitination involves the enzymatic cascade of E1, E2 and E3 enzymes that conjugate ubiquitin to lysine residues giving rise to monomeric ubiquitination and polymeric ubiquitination. Emerging research has established expansion of the ubiquitin code by non-canonical ubiquitination of N-termini and cysteine, serine and threonine residues. Generic methods for identifying ubiquitin substrates using mass spectrometry based proteomics often overlook non-canonical ubiquitinated substrates, suggesting that numerous undiscovered substrates of this modification exist. Moreover, there is a knowledge gap between in vitro studies and comprehensive understanding of the functional consequence of non-canonical ubiquitination in vivo. Here, we discuss the current knowledge about non-lysine ubiquitination, strategies to map the ubiquitinome and their applicability for studying non-canonical ubiquitination substrates and sites. Furthermore, we elucidate the available chemical biology toolbox and elaborate on missing links required to further unravel this less explored subsection of the ubiquitin system.

IMBAS-MS Discovers Organ-Specific HLA Peptide Patterns in Plasma

Distinction of non-self from self is the major task of the immune system. Immunopeptidomics studies the peptide repertoire presented by the human leukocyte antigen (HLA) protein, usually on tissues. However, HLA peptides are also bound to plasma soluble HLA (sHLA), but little is known about their origin and potential for biomarker discovery in this readily available biofluid. Currently, immunopeptidomics is hampered by complex workflows and limited sensitivity, typically requiring several mL of plasma. Here, we take advantage of recent improvements in the throughput and sensitivity of mass spectrometry (MS)-based proteomics to develop a highly sensitive, automated, and economical workflow for HLA peptide analysis, termed Immunopeptidomics by Biotinylated Antibodies and Streptavidin (IMBAS). IMBAS-MS quantifies more than 5000 HLA class I peptides from only 200 μl of plasma, in just 30 min. Our technology revealed that the plasma immunopeptidome of healthy donors is remarkably stable throughout the year and strongly correlated between individuals with overlapping HLA types. Immunopeptides originating from diverse tissues, including the brain, are proportionately represented. We conclude that sHLAs are a promising avenue for immunology and potentially for precision oncology.

β-arrestin1 is an E3 ubiquitin ligase adaptor for substrate linear polyubiquitination

G protein-coupled receptor (GPCR) signaling and trafficking are regulated by multiple mechanisms, including posttranslational modifications such as ubiquitination by E3 ubiquitin ligases. E3 ligases have been linked to agonist-stimulated ubiquitination of GPCRs via simultaneous binding to βarrestins. In addition, βarrestins have been suggested to assist E3 ligases for ubiquitination of key effector molecules, yet mechanistic insight is lacking. Here, we developed an in vitro reconstituted system and show that βarrestin1 (βarr1) serves as an adaptor between the effector protein signal-transducing adaptor molecule 1 (STAM1) and the E3 ligase atrophin-interacting protein 4. Via mass spectrometry, we identified seven lysine residues within STAM1 that are ubiquitinated and several types of ubiquitin linkages. We provide evidence that βarr1 facilitates the formation of linear polyubiquitin chains at lysine residue 136 on STAM1. This lysine residue is important for stabilizing the βarr1:STAM1 interaction in cells following GPCR activation. Our study identifies atrophin-interacting protein 4 as only the second E3 ligase known to conjugate linear polyubiquitin chains and a possible role for linear ubiquitin chains in GPCR signaling and trafficking.

Deciphering the protein ubiquitylation system in plants

Protein ubiquitylation is a post-translational modification (PTM) process that covalently modifies a protein substrate with either mono-ubiquitin moieties or poly-ubiquitin chains often at the lysine residues. In Arabidopsis, bioinformatic predictions have suggested that over 5% of its proteome constitutes the protein ubiquitylation system. Despite advancements in functional genomic studies in plants, only a small fraction of this bioinformatically predicted system has been functionally characterized. To expand our understanding about the regulatory function of protein ubiquitylation to that rivalling several other major systems, such as transcription regulation and epigenetics, I describe the status, issues, and new approaches of protein ubiquitylation studies in plant biology. I summarize the methods utilized in defining the ubiquitylation machinery by bioinformatics, identifying ubiquitylation substrates by proteomics, and characterizing the ubiquitin E3 ligase-substrate pathways by functional genomics. Based on the functional and evolutionary analyses of the F-box gene superfamily, I propose a deleterious duplication model for the large expansion of this family in plant genomes. Given this model, I present new perspectives of future functional genomic studies on the plant ubiquitylation system to focus on core and active groups of ubiquitin E3 ligase genes.

An adaptive stress response that confers cellular resilience to decreased ubiquitination

Ubiquitination is a post-translational modification initiated by the E1 enzyme UBA1, which transfers ubiquitin to ~35 E2 ubiquitin-conjugating enzymes. While UBA1 loss is cell lethal, it remains unknown how partial reduction in UBA1 activity is endured. Here, we utilize deep-coverage mass spectrometry to define the E1-E2 interactome and to determine the proteins that are modulated by knockdown of UBA1 and of each E2 in human cells. These analyses define the UBA1/E2-sensitive proteome and the E2 specificity in protein modulation. Interestingly, profound adaptations in peroxisomes and other organelles are triggered by decreased ubiquitination. While the cargo receptor PEX5 depends on its mono-ubiquitination for binding to peroxisomal proteins and importing them into peroxisomes, we find that UBA1/E2 knockdown induces the compensatory upregulation of other PEX proteins necessary for PEX5 docking to the peroxisomal membrane. Altogether, this study defines a homeostatic mechanism that sustains peroxisomal protein import in cells with decreased ubiquitination capacity.

Proteomic approaches advancing targeted protein degradation

Targeted protein degradation (TPD) is an emerging modality for research and therapeutics. Most TPD approaches harness cellular ubiquitin-dependent proteolytic pathways. Proteolysis-targeting chimeras (PROTACs) and molecular glue (MG) degraders (MGDs) represent the most advanced TPD approaches, with some already used in clinical settings. Despite these advances, TPD still faces many challenges, pertaining to both the development of effective, selective, and tissue-penetrant degraders and understanding their mode of action. In this review, we focus on progress made in addressing these challenges. In particular, we discuss the utility and application of recent proteomic approaches as indispensable tools to enable insights into degrader development, including target engagement, degradation selectivity, efficacy, safety, and mode of action.

Advances in data-independent acquisition mass spectrometry towards comprehensive digital proteome landscape

The data-independent acquisition mass spectrometry (DIA-MS) has rapidly evolved as a powerful alternative for highly reproducible proteome profiling with a unique strength of generating permanent digital maps for retrospective analysis of biological systems. Recent advancements in data analysis software tools for the complex DIA-MS/MS spectra coupled to fast MS scanning speed and high mass accuracy have greatly expanded the sensitivity and coverage of DIA-based proteomics profiling. Here, we review the evolution of the DIA-MS techniques, from earlier proof-of-principle of parallel fragmentation of all-ions or ions in selected m/z range, the sequential window acquisition of all theoretical mass spectra (SWATH-MS) to latest innovations, recent development in computation algorithms for data informatics, and auxiliary tools and advanced instrumentation to enhance the performance of DIA-MS. We further summarize recent applications of DIA-MS and experimentally-derived as well as in silico spectra library resources for large-scale profiling to facilitate biomarker discovery and drug development in human diseases with emphasis on the proteomic profiling coverage. Toward next-generation DIA-MS for clinical proteomics, we outline the challenges in processing multi-dimensional DIA data set and large-scale clinical proteomics, and continuing need in higher profiling coverage and sensitivity.

Serial and multi-level proteome analysis for microscale protein samples

Post-translational modifications (PTMs), such as phosphorylation and ubiquitination, play key roles in signal transduction and protein homeostasis. The crosstalk of PTMs greatly expands the components of proteome and protein functions. Multi-level proteome analysis, which involves proteome investigations of total lysate and PTMs in this context, provides a comprehensive approach to explore the PTM crosstalk of a biological system under diverse disturbances. However, multi-level proteome practice remains technically challenging. Here we intended to build a strategy for multi-level proteome analysis, in which we focus on the serial profiling the total proteome, ubiquitinome and phosphoproteome from the microscale of starting material. We started by evaluating five common lysis buffers and found that the sodium deoxycholate buffer provided the best overall performance. We then developed an approach for serial enrichment and profiling of the multi-level proteome. To expand the depth of identification, we customized the variable windows to perform data-independent acquisition (DIA) sequencing for each proteome. In total, we identified 6465 proteins, ∼20,000 GlyGly sites (class 1), and ∼ 19,000 phosphosites (class 1) sequentially using 1 mg of HeLa digest by three DIA measurements. We applied this strategy to analyze MG132-treated HeLa cells and observed the crosstalk between ubiquitination and phosphorylation. Our method can be referenced for other multi-level proteome studies with microscale samples. SIGNIFICANCE: Lysis buffer containing sodium deoxycholate provided the best overall performance in multi-level proteome analysis. One step of ubiquitination enrichment before phosphorylation enrichment does not reduce the reproducibility of phosphoproteome. Customized isolation windows were established for DIA analysis on each level of proteome. Combined the serial enrichment approach and the customized single-shot DIA method enabled the multi-level proteome of microscale protein samples.

Multi-omics profiling reveals rhythmic liver function shaped by meal timing

Post-translational modifications (PTMs) couple feed-fast cycles to diurnal rhythms. However, it remains largely uncharacterized whether and how meal timing organizes diurnal rhythms beyond the transcriptome. Here, we systematically profile the daily rhythms of the proteome, four PTMs (phosphorylation, ubiquitylation, succinylation and N-glycosylation) and the lipidome in the liver from young female mice subjected to either day/sleep time-restricted feeding (DRF) or night/wake time-restricted feeding (NRF). We detect robust daily rhythms among different layers of omics with phosphorylation the most nutrient-responsive and succinylation the least. Integrative analyses reveal that clock regulation of fatty acid metabolism represents a key diurnal feature that is reset by meal timing, as indicated by the rhythmic phosphorylation of the circadian repressor PERIOD2 at Ser971 (PER2-pSer971). We confirm that PER2-pSer971 is activated by nutrient availability in vivo. Together, this dataset represents a comprehensive resource detailing the proteomic and lipidomic responses by the liver to alterations in meal timing.

Deubiquitinase OTUD6A Regulates Innate Immune Response via Targeting UBC13

OTUD6A is a deubiquitinase that plays crucial roles in various human diseases. However, the precise regulatory mechanism of OTUD6A remains unclear. In this study, we found that OTUD6A significantly inhibited the production of type I interferon. Consistently, peritoneal macrophages and bone marrow-derived macrophages from Otud6a-/- mice produced more type I interferon after virus infection compared to cells from WT mice. Otud6a-/-- mice also exhibited increased resistance to lethal HSV-1 and VSV infections, as well as LPS attacks due to decreased inflammatory responses. Mechanistically, mass spectrometry results revealed that UBC13 was an OTUD6A-interacting protein, and the interaction was significantly enhanced after HSV-1 stimulation. Taken together, our findings suggest that OTUD6A plays a crucial role in the innate immune response and may serve as a potential therapeutic target for infectious disease.

Loss of N-terminal acetyltransferase A activity induces thermally unstable ribosomal proteins and increases their turnover in Saccharomyces cerevisiae

Protein N-terminal (Nt) acetylation is one of the most abundant modifications in eukaryotes, covering ~50-80 % of the proteome, depending on species. Cells with defective Nt-acetylation display a wide array of phenotypes such as impaired growth, mating defects and increased stress sensitivity. However, the pleiotropic nature of these effects has hampered our understanding of the functional impact of protein Nt-acetylation. The main enzyme responsible for Nt-acetylation throughout the eukaryotic kingdom is the N-terminal acetyltransferase NatA. Here we employ a multi-dimensional proteomics approach to analyze Saccharomyces cerevisiae lacking NatA activity, which causes global proteome remodeling. Pulsed-SILAC experiments reveals that NatA-deficient strains consistently increase degradation of ribosomal proteins compared to wild type. Explaining this phenomenon, thermal proteome profiling uncovers decreased thermostability of ribosomes in NatA-knockouts. Our data are in agreement with a role for Nt-acetylation in promoting stability for parts of the proteome by enhancing the avidity of protein-protein interactions and folding.

Deep learning from harmonized peptide libraries enables retention time prediction of diverse post translational modifications

In proteomics experiments, peptide retention time (RT) is an orthogonal property to fragmentation when assessing detection confidence. Advances in deep learning enable accurate RT prediction for any peptide from sequence alone, including those yet to be experimentally observed. Here we present Chronologer, an open-source software tool for rapid and accurate peptide RT prediction. Using new approaches to harmonize and false-discovery correct across independently collected datasets, Chronologer is built on a massive database with >2.2 million peptides including 10 common post-translational modification (PTM) types. By linking knowledge learned across diverse peptide chemistries, Chronologer predicts RTs with less than two-thirds the error of other deep learning tools. We show how RT for rare PTMs, such as OGlcNAc, can be learned with high accuracy using as few as 10-100 example peptides in newly harmonized datasets. This iteratively updatable workflow enables Chronologer to comprehensively predict RTs for PTM-marked peptides across entire proteomes.

Proteomic approaches to study ubiquitinomics

As originally described some 40 years ago, protein ubiquitination was thought to serve primarily as a static mark for protein degradation. In the ensuing years, it has become clear that 'ubiquitination' is a structurally diverse and dynamic post-translational modification and is intricately involved in a myriad of signaling pathways in all eukaryote cells. And like other key pathways in the functional proteome, ubiquitin signaling is often disrupted, sometimes severely so, in human pathophysiology. As a result of its central role in normal physiology and human disease, the ubiquitination field is now represented across the full landscape of biomedical research from fundamental structural and biochemical studies to translational and clinical research. In recent years, mass spectrometry has emerged as a powerful technology for the detection and characterization of protein ubiquitination. Herein we detail qualitative and quantitative proteomic methods using a compare/contrast approach to highlight their strengths and weaknesses.

Evaluation of DDA Library-Free Strategies for Phosphoproteomics and Ubiquitinomics Data-Independent Acquisition Data

Phosphoproteomics and ubiquitinomics data-independent acquisition (DIA) mass spectrometry (MS) data is typically analyzed by using a data-dependent acquisition (DDA) spectral library. The performance of various library-free strategies for analyzing phosphoproteomics and ubiquitinomics DIA MS data has not been evaluated. In this study, we systematically compare four commonly used DDA library-free approaches including Spectronaut's directDIA, DIA-Umpire, DIA-MSFragger, and in silico-predicted library for analysis of phosphoproteomics SWATH, DIA, and diaPASEF data as well as ubiquitinomics diaPASEF data. Spectronaut's directDIA shows the highest sensitivity for phosphopeptide detection not only in synthetic phosphopeptide samples but also in phosphoproteomics SWATH-MS and DIA data from real biological samples, when compared to the other three library-free strategies. For phosphoproteomics diaPASEF data, Spectronaut's directDIA and the in silico-predicted library based on DIA-NN identify almost the same number of phosphopeptides as a project-specific DDA spectral library. However, only about 30% of the total phosphopeptides are commonly identified, suggesting that the library-free strategies for phospho-diaPASEF data need further improvement in terms of sensitivity. For ubiquitinomics diaPASEF data, the in silico-predicted library performs the best among the four workflows and detects ∼50% more K-GG peptides than a project-specific DDA spectral library. Our results demonstrate that Spectronaut's directDIA is suitable for the analysis of phosphoproteomics SWATH-MS and DIA MS data, while the in silico-predicted library based on DIA-NN shows substantial advantages for ubiquitinomics diaPASEF MS data.

Does the Ubiquitination Degradation Pathway Really Reach inside of the Chloroplast? A Re-Evaluation of Mass Spectrometry-Based Assignments of Ubiquitination

A recent paper in Science Advances by Sun et al. claims that intra-chloroplast proteins in the model plant Arabidopsis can be polyubiquitinated and then extracted into the cytosol for subsequent degradation by the proteasome. Most of this conclusion hinges on several sets of mass spectrometry (MS) data. If the proposed results and conclusion are true, this would be a major change in the proteolysis/proteostasis field, breaking the long-standing dogma that there are no polyubiquitination mechanisms within chloroplast organelles (nor in mitochondria). Given its importance, we reanalyzed their raw MS data using both open and closed sequence database searches and encountered many issues not only with the results but also discrepancies between stated methods (e.g., use of alkylating agent iodoacetamide (IAA)) and observed mass modifications. Although there is likely enrichment of ubiquitination signatures in a subset of the data (probably from ubiquitination in the cytosol), we show that runaway alkylation with IAA caused extensive artifactual modifications of N termini and lysines to the point that a large fraction of the desired ubiquitination signatures is indistinguishable from artifactual acetamide signatures, and thus, no intra-chloroplast polyubiquitination conclusions can be drawn from these data. We provide recommendations on how to avoid such perils in future work.

Antibody-free approach for ubiquitination profiling by selectively clicking the ubiquitination sites

Ubiquitination is a reversible post-translational modification that plays a pivotal role in numerous biological processes. Antibody-based approaches, as the most used methods for identifying ubiquitination sites, exist sequence recognition bias, high cost, and ubiquitin-like protein modification interference, limiting their widespread application. Here, we proposed an Antibody-Free approach for Ubiquitination Profiling, termed AFUP, by selectively clicking the ubiquitinated lysine to enrich and profile endogenous ubiquitinated peptides using mass spectrometry. Briefly, protein amines were blocked with formaldehyde, and then the ubiquitin molecules were hydrolyzed from the ubiquitinated proteins by non-specific deubiquitinases USP2 and USP21 to release the free ε-amine of lysine. Peptides containing free ε-amines were selectively enriched with streptavidin beads upon NHS-SS-biotin labeling. Finally, the enriched peptides were eluted by DTT and analyzed by LC-MS/MS, resulting in ubiquitination profiling. Preliminary experiment showed that 349 ± 7 ubiquitination sites were identified in 0.8 mg HeLa lysates with excellent reproducibility (CV = 2%) and high quantitative stability (Pearson, r ≥ 0.91) using our method. With the combination of AFUP and simple basic C18 pre-fractionation, approximately 4000 ubiquitination sites were identified in a single run of 293T cells. In addition, we showed that 209 ubiquitination sites were significantly regulated in UBE2O knockdown cells after normalized to protein abundance. In conclusion, our results demonstrated that AFUP is a robust alternative strategy for ubiquitomics research.

In-depth analysis of the Sirtuin 5-regulated mouse brain malonylome and succinylome using library-free data-independent acquisitions

Post-translational modifications (PTMs) dynamically regulate proteins and biological pathways, typically through the combined effects of multiple PTMs. Lysine residues are targeted for various PTMs, including malonylation and succinylation. However, PTMs offer specific challenges to mass spectrometry-based proteomics during data acquisition and processing. Thus, novel and innovative workflows using data-independent acquisition (DIA) ensure confident PTM identification, precise site localization, and accurate and robust label-free quantification. In this study, we present a powerful approach that combines antibody-based enrichment with comprehensive DIA acquisitions and spectral library-free data processing using directDIA (Spectronaut). Identical DIA data can be used to generate spectral libraries and comprehensively identify and quantify PTMs, reducing the amount of enriched sample and acquisition time needed, while offering a fully automated workflow. We analyzed brains from wild-type and Sirtuin 5 (SIRT5)-knock-out mice, and discovered and quantified 466 malonylated and 2211 succinylated peptides. SIRT5 regulation remodeled the acylomes by targeting 164 malonylated and 578 succinylated sites. Affected pathways included carbohydrate and lipid metabolisms, synaptic vesicle cycle, and neurodegenerative diseases. We found 48 common SIRT5-regulated malonylation and succinylation sites, suggesting potential PTM crosstalk. This innovative and efficient workflow offers deeper insights into the mouse brain lysine malonylome and succinylome.

Site-specific proteomic strategies to identify ubiquitin and SUMO modifications: Challenges and opportunities

Ubiquitin and SUMO modify thousands of substrates to regulate most cellular processes. System-wide identification of ubiquitin and SUMO substrates provides global understanding of their cellular functions. In this review, we discuss the biological importance of site-specific modifications by ubiquitin and SUMO regulating the DNA damage response, protein quality control and cell cycle progression. Furthermore we discuss the machinery responsible for these modifications and methods to purify and identify ubiquitin and SUMO modified sites by mass spectrometry. We provide a framework to aid in the selection of appropriate purification, digestion and acquisition strategies suited to answer different biological questions. We highlight opportunities in the field for employing innovative technologies, as well as discuss challenges and long-standing questions in the field that are difficult to address with the currently available tools, emphasizing the need for further innovation.

Site-specific quantitative cysteine profiling with data-independent acquisition-based mass spectrometry

Chemical proteomics methods, such as activity-based protein profiling, have emerged as powerful and versatile tools to annotate the protein functions and targets of bioactive small molecules in complex biological systems. Incorporated with mass spectrometry (MS)-based quantitative proteomics method, changes of protein activities could be captured and investigated with site-specific precision. However, the semi-stochastic nature of data-dependent acquisition and high cost of the isotopic-labeled reagents make it challenging for chemical biology research to systematically and reproducibly analyze a large number of samples in multidimensional analysis and high-throughput screening. In this chapter, we describe an efficient quantitative chemical proteomic strategy, termed DIA-ABPP, with good reproducibility and high quantification accuracy. Cysteinome profiling was used as a proof-of-concept example with the detailed protocol to demonstrate the workflow of the DIA-ABPP method, including dose-dependent analysis of cysteines that are sensitive to modification by a reactive metabolite, screening of a cysteine-reactive fragment library, and profiling of circadian cysteinome fluctuation. This quantitative chemoproteomic strategy would provide an opportunity for in-depth multi-dimensional chemical proteomic profiling and illuminate the function of bioactive small molecules and proteins in complex biological systems.

Circadian signatures of adipose tissue in diet-induced obesity

High-fat diet (HFD) feeding rewires circadian rhythms of peripheral organs including the liver and adipose tissue. While the liver has been extensively studied, it remains largely unknown whether and how HFD organizes circadian biology in adipose tissue. Here, we took a systems approach to profile the diurnal transcriptome of adipose tissue in diet-induced obese mice either fed a low-fat diet (LFD) that reduces weight or still fed HFD. We detected about 200 and 2,500 diurnal genes in HFD and LFD, respectively. Pathway analysis revealed that rhythmic pathways in HFD are represented by circadian rhythm, ribosome biogenesis, and nucleosome organization, whereas those in LFD are represented by myeloid cell function. Remarkably, the majority of the circadian clock genes, except Clock, exhibited robust diurnal rhythm in the adipose tissue of HFD-fed mice. Analysis of mRNAs and proteins in another cohort of HFD-fed mice confirmed that Clock lost rhythmicity at the transcript, but not protein level. Diet reversal to LFD specifically restored diurnal difference of the Clock transcripts in adipose tissue. We matched transcriptomics data with global profiling of neutral lipids and found that lipid metabolism catalyzed by triglycerol hydrolase Ces1d is a key circadian feature that is activated by diet reversal. Together, our work defines the circadian signatures in the adipose tissue of diet-induced obese mice, and their flexibility upon dietary intervention, thereby shedding light on potential clock-modulated tissue-specific pathways during obesity.

HypDB: A functionally annotated web-based database of the proline hydroxylation proteome

Proline hydroxylation (Hyp) regulates protein structure, stability, and protein-protein interaction. It is widely involved in diverse metabolic and physiological pathways in cells and diseases. To reveal functional features of the Hyp proteome, we integrated various data sources for deep proteome profiling of the Hyp proteome in humans and developed HypDB (https://www.HypDB.site), an annotated database and web server for Hyp proteome. HypDB provides site-specific evidence of modification based on extensive LC-MS analysis and literature mining with 14,413 nonredundant Hyp sites on 5,165 human proteins including 3,383 Class I and 4,335 Class II sites. Annotation analysis revealed significant enrichment of Hyp on key functional domains and tissue-specific distribution of Hyp abundance across 26 types of human organs and fluids and 6 cell lines. The network connectivity analysis further revealed a critical role of Hyp in mediating protein-protein interactions. Moreover, the spectral library generated by HypDB enabled data-independent analysis (DIA) of clinical tissues and the identification of novel Hyp biomarkers in lung cancer and kidney cancer. Taken together, our integrated analysis of human proteome with publicly accessible HypDB revealed functional diversity of Hyp substrates and provides a quantitative data source to characterize Hyp in pathways and diseases.

Current methodologies in protein ubiquitination characterization: from ubiquitinated protein to ubiquitin chain architecture

Ubiquitination is a versatile post-translational modification (PTM), which regulates diverse fundamental features of protein substrates, including stability, activity, and localization. Unsurprisingly, dysregulation of the complex interaction between ubiquitination and deubiquitination leads to many pathologies, such as cancer and neurodegenerative diseases. The versatility of ubiquitination is a result of the complexity of ubiquitin (Ub) conjugates, ranging from a single Ub monomer to Ub polymers with different length and linkage types. To further understand the molecular mechanism of ubiquitination signaling, innovative strategies are needed to characterize the ubiquitination sites, the linkage type, and the length of Ub chain. With advances in chemical biology tools, computational methodologies, and mass spectrometry, protein ubiquitination sites and their Ub chain architecture have been extensively revealed. The obtained information on protein ubiquitination helps to crack the molecular mechanism of ubiquitination in numerous pathologies. In this review, we summarize the recent advances in protein ubiquitination analysis to gain updated knowledge in this field. In addition, the current and future challenges and barriers are also reviewed and discussed.

Rapid and in-depth coverage of the (phospho-)proteome with deep libraries and optimal window design for dia-PASEF

Data-independent acquisition (DIA) methods have become increasingly attractive in mass spectrometry–based proteomics because they enable high data completeness and a wide dynamic range. Recently, we combined DIA with parallel accumulation–serial fragmentation (dia-PASEF) on a Bruker trapped ion mobility (IM) separated quadrupole time-of-flight mass spectrometer. This requires alignment of the IM separation with the downstream mass selective quadrupole, leading to a more complex scheme for dia-PASEF window placement compared with DIA. To achieve high data completeness and deep proteome coverage, here we employ variable isolation windows that are placed optimally depending on precursor density in the m/z and IM plane. This is implemented in the freely available py_diAID (Python package for DIA with an automated isolation design) package. In combination with in-depth project-specific proteomics libraries and the Evosep liquid chromatography system, we reproducibly identified over 7700 proteins in a human cancer cell line in 44 min with quadruplicate single-shot injections at high sensitivity. Even at a throughput of 100 samples per day (11 min liquid chromatography gradients), we consistently quantified more than 6000 proteins in mammalian cell lysates by injecting four replicates. We found that optimal dia-PASEF window placement facilitates in-depth phosphoproteomics with very high sensitivity, quantifying more than 35,000 phosphosites in a human cancer cell line stimulated with an epidermal growth factor in triplicate 21 min runs. This covers a substantial part of the regulated phosphoproteome with high sensitivity, opening up for extensive systems-biological studies.

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Optimal dia-PASEF window design with py_diAID combined with deep libraries.

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Quantification of the HeLa cell proteome to a depth of >7700 in only 44 min.

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Ion mobility–resolved phosphoproteomics determines >35,000 class I phosphosites.

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py_diAID is freely available as GUI, CLI, and Python modules.

Post-translational Modifications: The Signals at the Intersection of Exercise, Glucose Uptake, and Insulin Sensitivity

Diabetes is a global epidemic, of which type 2 diabetes makes up the majority of cases. Nonetheless, for some individuals, type 2 diabetes is eminently preventable and treatable via lifestyle interventions. Glucose uptake into skeletal muscle increases during and in recovery from exercise, with exercise effective at controlling glucose homeostasis in individuals with type 2 diabetes. Furthermore, acute and chronic exercise sensitizes skeletal muscle to insulin. A complex network of signals converge and interact to regulate glucose metabolism and insulin sensitivity in response to exercise. Numerous forms of post-translational modifications (eg, phosphorylation, ubiquitination, acetylation, ribosylation, and more) are regulated by exercise. Here we review the current state of the art of the role of post-translational modifications in transducing exercise-induced signals to modulate glucose uptake and insulin sensitivity within skeletal muscle. Furthermore, we consider emerging evidence for noncanonical signaling in the control of glucose homeostasis and the potential for regulation by exercise. While exercise is clearly an effective intervention to reduce glycemia and improve insulin sensitivity, the insulin- and exercise-sensitive signaling networks orchestrating this biology are not fully clarified. Elucidation of the complex proteome-wide interactions between post-translational modifications and the associated functional implications will identify mechanisms by which exercise regulates glucose homeostasis and insulin sensitivity. In doing so, this knowledge should illuminate novel therapeutic targets to enhance insulin sensitivity for the clinical management of type 2 diabetes.

Serum Proteomic Analysis Identifies SAA1, FGA, SAP, and CETP as New Biomarkers for Eosinophilic Granulomatosis With Polyangiitis

Background

Eosinophilic granulomatosis with polyangiitis (EGPA) is characterized by asthma-like attacks in its early stage, which is easily misdiagnosed as severe asthma. Therefore, new biomarkers for the early diagnosis of EGPA are needed, especially for differentiating the diagnosis of asthma.

Objectives

To identify serum biomarkers that can be used for early diagnosis of EGPA and to distinguish EGPA from severe asthma.

Method

Data-independent acquisition (DIA) analysis was performed to identify 45 healthy controls (HC), severe asthma (S-A), and EGPA patients in a cohort to screen biomarkers for early diagnosis of EGPA and to differentiate asthma diagnosis. Subsequently, parallel reaction monitoring (PRM) analysis was applied to a validation cohort of 71 HC, S-A, and EGPA patients.

Result

Four candidate biomarkers were identified from DIA and PRM analysis-i.e., serum amyloid A1 (SAA1), fibrinogen-α (FGA), and serum amyloid P component (SAP)-and were upregulated in the EGPA group, while cholesteryl ester transfer protein (CETP) was downregulated in the EGPA group compared with the S-A group. Receiver operating characteristics analysis shows that, as biomarkers for early diagnosis of EGPA, the combination of SAA1, FGA, and SAP has an area under the curve (AUC) of 0.947, a sensitivity of 82.35%, and a specificity of 100%. The combination of SAA1, FGA, SAP, and CETP as biomarkers for differential diagnosis of asthma had an AUC of 0.921, a sensitivity of 78.13%, and a specificity of 100%, which were all larger than single markers. Moreover, SAA1, FGA, and SAP were positively and CETP was negatively correlated with eosinophil count.

Conclusion

DIA-PRM combined analysis screened and validated four previously unexplored but potentially useful biomarkers for early diagnosis of EGPA and differential diagnosis of asthma.

Dynamic human liver proteome atlas reveals functional insights into disease pathways

Deeper understanding of liver pathophysiology would benefit from a comprehensive quantitative proteome resource at cell type resolution to predict outcome and design therapy. Here, we quantify more than 150,000 sequence‐unique peptides aggregated into 10,000 proteins across total liver, the major liver cell types, time course of primary cell cultures, and liver disease states. Bioinformatic analysis reveals that half of hepatocyte protein mass is comprised of enzymes and 23% of mitochondrial proteins, twice the proportion of other liver cell types. Using primary cell cultures, we capture dynamic proteome remodeling from tissue states to cell line states, providing useful information for biological or pharmaceutical research. Our extensive data serve as spectral library to characterize a human cohort of non‐alcoholic steatohepatitis and cirrhosis. Dramatic proteome changes in liver tissue include signatures of hepatic stellate cell activation resembling liver cirrhosis and providing functional insights. We built a web‐based dashboard application for the interactive exploration of our resource (www.liverproteome.org).

The structural context of posttranslational modifications at a proteome-wide scale

The recent revolution in computational protein structure prediction provides folding models for entire proteomes, which can now be integrated with large-scale experimental data. Mass spectrometry (MS)-based proteomics has identified and quantified tens of thousands of posttranslational modifications (PTMs), most of them of uncertain functional relevance. In this study, we determine the structural context of these PTMs and investigate how this information can be leveraged to pinpoint potential regulatory sites. Our analysis uncovers global patterns of PTM occurrence across folded and intrinsically disordered regions. We found that this information can help to distinguish regulatory PTMs from those marking improperly folded proteins. Interestingly, the human proteome contains thousands of proteins that have large folded domains linked by short, disordered regions that are strongly enriched in regulatory phosphosites. These include well-known kinase activation loops that induce protein conformational changes upon phosphorylation. This regulatory mechanism appears to be widespread in kinases but also occurs in other protein families such as solute carriers. It is not limited to phosphorylation but includes ubiquitination and acetylation sites as well. Furthermore, we performed three-dimensional proximity analysis, which revealed examples of spatial coregulation of different PTM types and potential PTM crosstalk. To enable the community to build upon these first analyses, we provide tools for 3D visualization of proteomics data and PTMs as well as python libraries for data accession and processing.

Ubiquitinomics: history, methods and applications in basic research and drug discovery

The ubiquitin-proteasome system (UPS) was discovered about 40 years ago and is known to regulate a multitude of cellular processes including protein homeostasis. ubiquitylated proteins are recognized by downstream effectors, resulting in alterations of protein abundance, activity, or localization. Not surprisingly, the ubiquitylation machinery is dysregulated in numerous diseases, including cancers and neurodegeneration. Mass spectrometry (MS)-based proteomics has emerged as a transformative technology for characterizing protein ubiquitylation in an unbiased fashion. Here, we provide an overview of the different MS-based approaches for studying protein ubiquitylation. We review various methods for enriching and quantifying ubiquitin modifications at the peptide or protein level, outline MS acquisition and data processing approaches and discuss key challenges. Finally, we examine how MS-based ubiquitinomics can aid both basic biology and drug discovery research. This article is protected by copyright. All rights reserved.

The Next Frontier: Translational Development of Ubiquitination, SUMOylation, and NEDDylation in Cancer

Post-translational modifications of proteins ensure optimized cellular processes, including proteostasis, regulated signaling, cell survival, and stress adaptation to maintain a balanced homeostatic state. Abnormal post-translational modifications are associated with cellular dysfunction and the occurrence of life-threatening diseases, such as cancer and neurodegenerative diseases. Therefore, some of the frequently seen protein modifications have been used as disease markers, while others are targeted for developing specific therapies. The ubiquitin and ubiquitin-like post-translational modifiers, namely, small ubiquitin-like modifier (SUMO) and neuronal precursor cell-expressed developmentally down-regulated protein 8 (NEDD8), share several features, such as protein structures, enzymatic cascades mediating the conjugation process, and targeted amino acid residues. Alterations in the regulatory mechanisms lead to aberrations in biological processes during tumorigenesis, including the regulation of tumor metabolism, immunological modulation of the tumor microenvironment, and cancer stem cell stemness, besides many more. Novel insights into ubiquitin and ubiquitin-like pathways involved in cancer biology reveal a potential interplay between ubiquitination, SUMOylation, and NEDDylation. This review outlines the current understandings of the regulatory mechanisms and assay capabilities of ubiquitination, SUMOylation, and NEDDylation. It will further highlight the role of ubiquitination, SUMOylation, and NEDDylation in tumorigenesis.

ABPP-HT*-Deep Meets Fast for Activity-Based Profiling of Deubiquitylating Enzymes Using Advanced DIA Mass Spectrometry Methods

Activity-based protein profiling (ABPP) uses a combination of activity-based chemical probes with mass spectrometry (MS) to selectively characterise a particular enzyme or enzyme class. ABPP has proven invaluable for profiling enzymatic inhibitors in drug discovery. When applied to cell extracts and cells, challenging the ABP-enzyme complex formation with a small molecule can simultaneously inform on potency, selectivity, reversibility/binding affinity, permeability, and stability. ABPP can also be applied to pharmacodynamic studies to inform on cellular target engagement within specific organs when applied to in vivo models. Recently, we established separate high depth and high throughput ABPP (ABPP-HT) protocols for the profiling of deubiquitylating enzymes (DUBs). However, the combination of the two, deep and fast, in one method has been elusive. To further increase the sensitivity of the current ABPP-HT workflow, we implemented state-of-the-art data-independent acquisition (DIA) and data-dependent acquisition (DDA) MS analysis tools. Hereby, we describe an improved methodology, ABPP-HT* (enhanced high-throughput-compatible activity-based protein profiling) that in combination with DIA MS methods, allowed for the consistent profiling of 35-40 DUBs and provided a reduced number of missing values, whilst maintaining a throughput of 100 samples per day.

Post-Translational Modifications of G Protein–Coupled Receptors Revealed by Proteomics and Structural Biology

G protein–coupled receptors (GPCRs) are a protein superfamily comprising >800 members that regulate numerous cellular and physiologic responses. GPCRs represent the largest class of therapeutic targets with implications in various diseases. Although advances in GPCR structural and pharmacological research have significantly improved our knowledge of GPCR signaling mechanisms, mapping diverse post-translational modifications (PTMs) of GPCR proteins and understanding their regulatory roles have received much less attention. Mass spectrometry-based proteomics has become the most popular technology for profiling protein PTMs in a systematic manner. Herein we provide an overview of PTM types, locations, crosstalk and dynamic regulation for different GPCRs that are characterized using proteomic and/or biochemical approaches. Our main focus is on glycosylation, phosphorylation, ubiquitination and palmitoylation that are known to modulate receptor folding, biosynthesis, trafficking, dimerization and signaling. Furthermore, we discuss the locations of specific PTM sites in the structure of a given GPCR and its signaling complex to highlight the importance of PTM regulation in the molecular basis of GPCRs, which may shed new light on structure-based drug discovery.

Exercise mediates ubiquitin signalling in human skeletal muscle

Physical activity or regular exercise provides many beneficial effects towards human health, helping prevent and ameliorate metabolic diseases. However, certain molecular mechanisms that mediate these health benefits remain poorly understood. Parker et al. provided the first global analysis of exercise‐regulated ubiquitin signalling in human skeletal muscle, revealing post‐translational modification cross‐talk. As a result of their analysis, NEDDylation is thought to promote ubiquitin signalling for the removal of damaged proteins following exercise. The proteomic dataset generated from their study is invaluable for researchers in this field to validate new mechanistic hypotheses. To further reveal molecular mechanisms regulated by exercise, future research could employ more sensitive mass spectrometry‐based workflows that increase the detection of both ubiquitylated sites and peptides and subsequently identify more exercise‐regulated ubiquitin signalling pathways.

A proteomic perspective on TNF-mediated signalling and cell death

The tumour necrosis factor (TNF) is the most potent inducer of cell death amongst cytokines. It is crucial for processes including homeostasis, the development of the immune system and fighting infections. However, high levels of TNF due to genetic disorders or persistent infections can contribute to autoinflammatory and autoimmune diseases or life-threatening conditions like sepsis. These diseases generally display increased levels of cell death, which, downstream of the TNF receptor, can either be caspase-dependent (apoptosis) or caspase-independent (necroptosis). Significant efforts have been invested in unravelling and manipulating signalling mechanisms regulating these two different types of cell death. Here I discuss how modern proteomic approaches like phosphoproteomics and secretomics provide a novel perspective on this central cytokine and its effect on inflammation and cell survival.

UbE3-APA: a bioinformatic strategy to elucidate ubiquitin E3 ligase activities in quantitative proteomics study

MOTIVATION

Ubiquitination is widely involved in protein homeostasis and cell signaling. Ubiquitin E3 ligases are critical regulators of ubiquitination that recognize and recruit specific ubiquitination targets for the final rate-limiting step of ubiquitin transfer reactions. Understanding the ubiquitin E3 ligase activities will provide knowledge in the upstream regulator of the ubiquitination pathway and reveal potential mechanisms in biological processes and disease progression. Recent advances in mass spectrometry-based proteomics have enabled deep profiling of ubiquitylome in a quantitative manner. Yet, functional analysis of ubiquitylome dynamics and pathway activity remains challenging.

RESULTS

Here, we developed a UbE3-APA, a computational algorithm and stand-alone python-based software for Ub E3 ligase Activity Profiling Analysis. Combining an integrated annotation database with statistical analysis, UbE3-APA identifies significantly activated or suppressed E3 ligases based on quantitative ubiquitylome proteomics datasets. Benchmarking the software with published quantitative ubiquitylome analysis confirms the genetic manipulation of SPOP enzyme activity through overexpression and mutation. Application of the algorithm in the re-analysis of a large cohort of ubiquitination proteomics study revealed the activation of PARKIN and the co-activation of other E3 ligases in mitochondria depolarization-induced mitophagy process. We further demonstrated the application of the algorithm in the DIA (data-independent acquisition)-based quantitative ubiquitylome analysis.

AVAILABILITY AND IMPLEMENTATION

Source code and binaries are freely available for download at URL: https://github.com/Chenlab-UMN/Ub-E3-ligase-Activity-Profiling-Analysis, implemented in python and supported on Linux and MS Windows.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

A practical guide to interpreting and generating bottom-up proteomics data visualizations

Mass-spectrometry based bottom-up proteomics is the main method to analyze proteomes comprehensively and the rapid evolution of instrumentation and data analysis has made the technology widely available. Data visualization is an integral part of the analysis process and it is crucial for the communication of results. This is a major challenge due to the immense complexity of MS data. In this review, we provide an overview of commonly used visualizations, starting with raw data of traditional and novel MS technologies, then basic peptide and protein level analyses, and finally visualization of highly complex datasets and networks. We specifically provide guidance on how to critically interpret and discuss the multitude of different proteomics data visualizations. Furthermore, we highlight Python-based libraries and other open science tools that can be applied for independent and transparent generation of customized visualizations. To further encourage programmatic data visualization, we provide the Python code used to generate all data Figures in this review on GitHub (https://github.com/MannLabs/ProteomicsVisualization). This article is protected by copyright. All rights reserved.

Quantitative Chemoproteomic Profiling with Data-Independent Acquisition-Based Mass Spectrometry

Activity-based protein profiling (ABPP) has emerged as a powerful and versatile tool to enable annotation of protein functions and discovery of targets of bioactive ligands in complex biological systems. It utilizes chemical probes to covalently label functional sites in proteins so that they can be enriched for mass spectrometry (MS)-based quantitative proteomics analysis. However, the semistochastic nature of data-dependent acquisition and high cost associated with isotopically encoded quantification reagents compromise the power of ABPP in multidimensional analysis and high-throughput screening, when a large number of samples need to be quantified in parallel. Here, we combine the data-independent acquisition (DIA) MS with ABPP to develop an efficient label-free quantitative chemical proteomic method, DIA-ABPP, with good reproducibility and high accuracy for high-throughput quantification. We demonstrated the power of DIA-ABPP for comprehensive profiling of functional cysteineome in three distinct applications, including dose-dependent quantification of cysteines' sensitivity toward a reactive metabolite, screening of ligandable cysteines with a covalent fragment library, and profiling of cysteinome fluctuation in circadian clock cycles. DIA-ABPP will open new opportunities for in-depth and multidimensional profiling of functional proteomes and interactions with bioactive small molecules in complex biological systems.

Deep learning approaches for data-independent acquisition proteomics

INTRODUCTION

Data-independent acquisition (DIA) is an emerging technology for large-scale proteomic studies. DIA data analysis methods are evolving rapidly, and deep learning has cut a conspicuous figure in this field.

AREAS COVERED

This review discusses and provides an overview of the deep learning methods that are used for DIA data analysis, including spectral library prediction, feature scoring, and statistical control in peptide-centric analysis, as well as de novo peptide sequencing. Literature searches were performed for articles, including preprints, up to December 2021 from PubMed, Scopus, and Web of Science databases.

EXPERT OPINION

While spectral library prediction has broken through the limitation on proteome coverage of experimental libraries, the statistical burden due to the large query space is the remaining challenge of utilizing proteome-wide predicted libraries. Analysis of post-translational modifications is another promising direction of deep learning-based DIA methods.

Extracellular Vesicle Proteome in Prostate Cancer: A Comparative Analysis of Mass Spectrometry Studies

Molecular diagnostics based on discovery research holds the promise of improving screening methods for prostate cancer (PCa). Furthermore, the congregated information prompts the question whether the urinary extracellular vesicles (uEV) proteome has been thoroughly explored, especially at the proteome level. In fact, most extracellular vesicles (EV) based biomarker studies have mainly targeted plasma or serum. Therefore, in this study, we aim to inquire about possible strategies for urinary biomarker discovery particularly focused on the proteome of urine EVs. Proteomics data deposited in the PRIDE archive were reanalyzed to target identifications of potential PCa markers. Network analysis of the markers proposed by different prostate cancer studies revealed moderate overlap. The recent throughput improvements in mass spectrometry together with the network analysis performed in this study, suggest that a larger standardized cohort may provide potential biomarkers that are able to fully characterize the heterogeneity of PCa. According to our analysis PCa studies based on urinary EV proteome presents higher protein coverage compared to plasma, plasma EV, and voided urine proteome. This together with a direct interaction of the prostate gland and urethra makes uEVs an attractive option for protein biomarker studies. In addition, urinary proteome based PCa studies must also evaluate samples from bladder and renal cancers to assess specificity for PCa.

Tools for Decoding Ubiquitin Signaling in DNA Repair

The maintenance of genome stability requires dedicated DNA repair processes and pathways that are essential for the faithful duplication and propagation of chromosomes. These DNA repair mechanisms counteract the potentially deleterious impact of the frequent genotoxic challenges faced by cells from both exogenous and endogenous agents. Intrinsic to these mechanisms, cells have an arsenal of protein factors that can be utilised to promote repair processes in response to DNA lesions. Orchestration of the protein factors within the various cellular DNA repair pathways is performed, in part, by post-translational modifications, such as phosphorylation, ubiquitin, SUMO and other ubiquitin-like modifiers (UBLs). In this review, we firstly explore recent advances in the tools for identifying factors involved in both DNA repair and ubiquitin signaling pathways. We then expand on this by evaluating the growing repertoire of proteomic, biochemical and structural techniques available to further understand the mechanistic basis by which these complex modifications regulate DNA repair. Together, we provide a snapshot of the range of methods now available to investigate and decode how ubiquitin signaling can promote DNA repair and maintain genome stability in mammalian cells.

The role of proteomics in the multiplexed analysis of gene alterations in human cancer

INTRODUCTION

Proteomics has played a pivotal role in identifying proteins perturbed in disease conditions when compared with healthy samples. Study of dysregulated proteins aids in identifying diagnostic markers and potential therapeutic targets. Cancer is an outcome of interplay of several such disarrayed proteins and molecular pathways which perturb cellular homeostasis, resulting in transformation. In this review, we discuss various facets of proteomic approaches, including tools and technological advancements, aiding in understanding differentially expressed molecules and signaling mechanisms.

AREAS COVERED

In this review, we have taken the approach of documenting the different methods of proteomic studies, ranging from labeling techniques, data analysis methods, and the nature of molecule detected. We summarize each technique and provide a glimpse of cancer research carried out using them, highlighting the advantages and drawbacks in comparison with others. Literature search using online resources, such as PubMed and Google Scholar were carried out for this approach.

EXPERT OPINION

Technological advancements in proteomics studies have come a long way from the study of two-dimensional mapping of proteins separated on gels in the early 1970s. Higher precision in molecular identification and quantification (high throughput), and greater number of samples analyzed have been the focus of researchers.

Automating UbiFast for High-throughput and Multiplexed Ubiquitin Enrichment

Robust methods for deep-scale enrichment and site-specific identification of ubiquitylation sites are necessary for characterizing the myriad roles of protein ubiquitylation. To this end we previously developed UbiFast, a sensitive method for highly multiplexed ubiquitylation profiling where K-ϵ-GG peptides are enriched with anti-K-ε-GG antibody and labeled on-antibody with isobaric labeling reagents for sample multiplexing. Here, we present robotic automation of the UbiFast method using a magnetic bead-conjugated K-ε-GG antibody (mK-ε-GG) and a magnetic particle processor. We report the identification of ∼20,000 ubiquitylation sites from a TMT10-plex with 500 μg input per sample processed in ∼2 h. Automation of the UbiFast method greatly increased the number of identified and quantified ubiquitylation sites, improved reproducibility, and significantly reduced processing time. The automated method also significantly reduced variability across process replicates compared with the manual method. The workflow enables processing of up to 96 samples in a single day making it suitable to study ubiquitylation in large sample sets. Here we demonstrate the applicability of the method to profile small amounts of tissue using breast cancer patient–derived xenograft (PDX) tissue samples.

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HS mag anti-K-ε-GG antibody increases sensitivity of ubiquitylation site detection.

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Automated UbiFast increases reproducibility and sample processing throughput.

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The automated UbiFast workflow enables processing of up to 96 samples in one day.

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UbiFast can be employed to profile ubiquitylomes from small amounts of tumor tissue.